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Graphing Continuous Data
For graphing continuous data, there are several options that effectively represent the data’s range and distribution. Here are some recommended methods:
Histogram
A histogram displays the frequency distribution of continuous data by dividing the data into intervals (bins) and plotting the number of data points that fall into each interval. Provides a clear view of the data distribution and allows you to see patterns such as skewness or modality.
Ideal for showing the distribution of data, such as the range of test scores or measurements.
Line Graph
A line graph plots data points on a Cartesian plane and connects them with a continuous line. Useful for displaying trends over time or continuous relationships between variables. Best for showing how continuous data changes over a period, such as temperature changes throughout the day or stock prices over time.
Scatter Plot
A scatter plot displays data points on a Cartesian plane to show the relationship between two continuous variables. Helps identify correlations or patterns between variables, and can show the spread and clustering of data points. Suitable for exploring relationships between two continuous variables, such as height vs. weight or time vs. speed.
Box Plot (Box-and-Whisker Plot)
A box plot displays the median, quartiles, and potential outliers of continuous data. Provides a summary of the data distribution and highlights variability and outliers. Useful for comparing distributions between groups or understanding the spread and central tendency of continuous data.
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